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X Demographics
Mendeley readers
Attention Score in Context
| Chapter title |
Resources for Assignment of Phosphorylation Sites on Peptides and Proteins.
|
|---|---|
| Chapter number | 20 |
| Book title |
Phospho-Proteomics
|
| Published in |
Methods in molecular biology, January 2016
|
| DOI | 10.1007/978-1-4939-3049-4_20 |
| Pubmed ID | |
| Book ISBNs |
978-1-4939-3048-7, 978-1-4939-3049-4
|
| Authors |
Ravikumar, Vaishnavi, Macek, Boris, Mijakovic, Ivan, Vaishnavi Ravikumar, Boris Macek, Ivan Mijakovic |
| Editors |
Louise von Stechow |
| Abstract |
Reversible protein phosphorylation is a key regulatory posttranslational modification that plays a significant role in major cellular signaling processes. Phosphorylation events can be systematically identified, quantified, and localized on protein sequence using publicly available bioinformatic tools. Here we present the software tools commonly used by the phosphoproteomics community, discuss their underlying principles of operation, and provide a protocol for large-scale phosphoproteome data analysis using the MaxQuant software suite. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 13 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| France | 1 | 8% |
| Unknown | 12 | 92% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 3 | 23% |
| Professor > Associate Professor | 2 | 15% |
| Unspecified | 1 | 8% |
| Student > Doctoral Student | 1 | 8% |
| Lecturer > Senior Lecturer | 1 | 8% |
| Other | 2 | 15% |
| Unknown | 3 | 23% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 4 | 31% |
| Agricultural and Biological Sciences | 3 | 23% |
| Computer Science | 2 | 15% |
| Unspecified | 1 | 8% |
| Unknown | 3 | 23% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 21 November 2015.
All research outputs
#20,296,405
of 22,833,393 outputs
Outputs from Methods in molecular biology
#9,916
of 13,127 outputs
Outputs of similar age
#330,625
of 393,581 outputs
Outputs of similar age from Methods in molecular biology
#1,053
of 1,470 outputs
Altmetric has tracked 22,833,393 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 13,127 research outputs from this source. They receive a mean Attention Score of 3.4. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 393,581 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1,470 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.